Short-term wind speed forecast based on wavelet packet transform and LS-SVM

It is well known that large-capacity wind power, as a type of strong fluctuations and random power, has an impact on grid safety. Due to this situation, accurate wind speed forecast plays an important role in reducing the impact of wind power on the grid. In this paper, we discuss the short-term wind speed forecast problem based on the wavelet packet transform and least squares support vector machine (LS-SVM). Firstly, high-frequency and low-frequency signals of wind speed are analyzed by the wavelet packet algorithm. Then, optimal wavelet packet transform is selected by minimum entropy principle. Based on these, short-term wind speed forecast model is established by LS-SVM. As an application of the proposed method, a case study with the actual data of a wind farm is presented to show the efficiency and accuracy compared with the previous results.